Free
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Skim AI is an AI-powered platform designed to help businesses win public tender applications. It provides access to thousands of European tenders daily with personalized alerts, automated summaries, and centralized tracking. Skim AI automates RFP applications, reducing the time required from days to minutes by leveraging prior RFP applications. It uses AI to find, manage, and bid on government contracts, streamlining the tender process from search to submission.
To use Skim AI, search for relevant public sector tenders, qualify leads using TenderGPT, manage compliance requirements, and draft RFP responses with the AI-powered writer. The platform streamlines the entire tender lifecycle from start to finish.
Skim uses AI to help businesses identify public sector tenders, manage compliance, and submit competitive government contract bids.
Skim drafts your proposal in seconds by training on your past winning bids, which saves your team time and helps you meet tight deadlines.
While most government tender tools focus on a single task like searching or writing, Skim integrates the entire process—including search, tracking, collaboration, and AI-powered proposal writing—into one platform.
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Free plan available.
Use these comparison pages to understand the trade-offs between the models most relevant to Skim AI.
Compare GPT 5.4 and GPT 5.4 Pro across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare GPT 5.5 and GPT 5.4 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare GPT 5.5 and Claude 4.6 Opus across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare GPT 5.5 and Claude 4.6 Sonnet across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
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